Non-iterative image feature matching algorithm based on reference point correspondences

Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity（D） of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.

基于子图灰度比较的匹配模板选取算法

为降低图像匹配模板选取算法的时间复杂度,提出一种基于子图灰度比较编码的图像匹配模板选取算法。首先将子图等分为2×2子块,以子图及邻近区域的4×4子块的灰度比较关系为子图赋予一个编码;其次在所有子图编码中选取重复次数最少的编码对应的一个子图或若干个子图中图像方差最大者作为匹配模板。算法复杂度分析和仿真实验结果表明,该匹配模板选取算法在保证了一定的有效性的前提下,其时间复杂度优于若干常用匹配模板选取准则。

循环链码与实物检验皮带秤的比较

本文针对皮带秤在火电厂生产使用过程中存在的问题,进行了具体的分析,确定长期困扰用户的原因,明确了循环链码不能直接检验皮带秤的概念,安装皮带秤的首次检定、皮带更换后的检定、皮带输送机大修后的检定、皮带秤的周期性检定都必须用实物检定的方法执行。循环链码只能作日常维护中的检验。我们只能利用它的重复性,而不是它的准确度。